Railway importance in the transportation industry is increasing continuously, due to the
growing demand of both passenger travel and transportation of goods. However, more than …

Owing to early diagnosis and treatment of cancer as a prerequisite in recent times, the role
of machine learning has been increased substantially. The mathematically powerful and …

Expert's knowledge base systems are not effective as a decision-making aid for physicians
in providing accurate diagnosis and treatment of heart diseases due to vagueness in …

Background We employed machine learning approaches to (I) determine distinct
progression trajectories in Parkinson's disease (PD)(unsupervised clustering task), and (II) …

Dissolved gas analysis (DGA) based in insulating oil has become a more mature method in
the field of transformer fault diagnosis. However, due to the complexity and diversity of fault …

SQL injection attack is considered one of the most dangerous vulnerabilities exploited to
leak sensitive information, gain unauthorized access, and cause financial loss to individuals …

Objectives The present work focuses on assessment of Parkinson's disease (PD), including
both PD subtype identification (unsupervised task) and prediction (supervised task). We …

Objectives It is important to subdivide Parkinson's disease (PD) into subtypes, enabling
potentially earlier disease recognition and tailored treatment strategies. We aimed to identify …

In this work, the modification of the probabilistic neural network (PNN) is proposed. The
traditional network is adjusted by introducing the weight coefficients between pattern and …

Fault diagnosis methods based on probabilistic neural networks (PNNs) have been widely
used in various products, owing to their simplicity and efficiency. However, in some multi …